Projects: Computational RNA and target identification / structural biology

It has been known for a number of years that RNA molecules not only exclusively convey hereditary information of the DNA into amino acid sequences, but also perform extensive regulatory functions themselves. Non-protein coding RNAs are thereby subdivided into two rough groups, ncRNAs with a nucleotide sequence length of less than 200 nt (short ncRNAs) and the novel long ncRNAs, which have a sequence length of more than 200 nt. The gene regulatory mechanisms of the short ncRNAs, such as miRNAs and snoRNAs, are usually very well explained, while functions are only described exemplarily for the group of long ncRNAs. Studies on individual long ncRNAs have shown that they control central cellular processes such as transcription and translation. Furthermore, they are also involved in sub-cellular localization, in the organization of cellular spatial structures and in the control of epigenetic modifications. We and others were able to show that long ncRNAs in various tissues and signal pathways associated with disease are specifically regulated. Novel therapies based on long ncRNAs could then have specific impact and produce smaller side effects than traditional approaches. With methods from the RNA computational biology and systems biology, such as the prediction, modelling and classification of RNA secondary structure motifs, as well as by evolutionary and transcription studies, we address the topic of which gene regulatory mechanisms control cellular processes by long ncRNAs that have been identified as biomarkers, and to what extent these are suitable as therapeutic targets.


School of Embedded Composite Artificial Intelligence (SECAI)